Systems and methods for processing electronic medical images to determine enhanced electronic medical images

ABSTRACT

Systems and methods for processing electronic images from a medical device comprise receiving a first image frame and a second image frame from a medical device, and determining a region of interest by subtracting the first image frame from the second image frame, the region of interest corresponding to a visual obstruction in the first image frame and/or second image frame. Image processing may be applied to the first image frame and/or second image frame based on a comparison between a first area of the first image frame corresponding to the region of interest and a second area of the second image frame corresponding to the region of interest, and the first image frame and/or second image frame may be provided for display to a user.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of priority from U.S. ProvisionalApplication No. 62/890,399, filed on Aug. 22, 2019, which isincorporated by reference herein in its entirety.

TECHNICAL FIELD

Various aspects of the present disclosure relate generally to systemsand methods useful in planning and/or performing medical procedures.

BACKGROUND

Substantial progress has been made towards increasing the effectivenessof medical treatment while reducing trauma and risks to the patient.Many procedures that once required open surgery now may be done withless invasive techniques, thus providing for less recovery time andrisks of infection for the patient. Certain procedures requiring biopsy,electro-stimulation, tissue ablation, or removal of native or foreignbodies may be performed through minimally-invasive surgery.

In the field of urology, for example, renal calculi or kidney stones canaccumulate in the urinary tract and become lodged in the kidney. Kidneystones are deposits of materials from the urine, typically minerals andacid salts. While smaller stones may pass from the body naturally,larger stones can require surgical intervention for removal. While opensurgery was once the standard treatment for the removal of stones, otherless invasive techniques, such as ureteroscopy and percutaneousnephrolithotomy/nephrolithotripsy (PCNL), have emerged as safer,effective alternatives. Additionally, advances in imaging technologyhave improved a medical professional's ability to identify and locatestones before and during procedures. Nevertheless, medical professionalsstill must analyze images to determine the location of stones andwhether any stones are present. Moreover, the images are oftenobstructed, blurry, and/or otherwise difficult to evaluate, making themedical professional's task of discerning the presence of any stoneschallenging.

The systems, devices, and methods of the current disclosure may rectifysome of the deficiencies described above, and/or address other aspectsof the prior art.

SUMMARY

Examples of the present disclosure relate to, among other things,medical systems and methods. Each of the examples disclosed herein mayinclude one or more of the features described in connection with any ofthe other disclosed examples.

In one example, the present disclosure includes a method for processingelectronic images from a medical device comprise receiving a first imageframe and a second image frame from a medical device, and determining aregion of interest by subtracting the first image frame from the secondimage frame, the region of interest corresponding to a visualobstruction in the first image frame and/or second image frame. Imageprocessing may be applied to the first image frame and/or second imageframe based on a comparison between a first area of the first imageframe corresponding to the region of interest and a second area of thesecond image frame corresponding to the region of interest, and thefirst image frame and/or second image frame may be provided for displayto a user.

In another example, the present disclosure includes a system forprocessing electronic images from a medical device, the systemcomprising a data storage device storing instructions for processingelectronic images, and a processor configured to execute theinstructions to perform a method for processing electronic images. Themethod may comprise receiving a first image frame and a second imageframe from a medical device, and determining a region of interest bysubtracting the first image frame from the second image frame, theregion of interest corresponding to a visual obstruction in the firstimage frame and/or second image frame. Image processing may be appliedto the first image frame and/or second image frame based on a comparisonbetween a first area of the first image frame corresponding to theregion of interest and a second area of the second image framecorresponding to the region of interest, and the first image frameand/or second image frame may be provided for display to a user.

In another example, the present disclosure includes a non-transitorycomputer-readable medium storing instructions that, when executed by acomputer, cause the computer to perform a method for processingelectronic images from a medical device. The method may comprisereceiving a first image frame and a second image frame from a medicaldevice, and determining a region of interest by subtracting the firstimage frame from the second image frame, the region of interestcorresponding to a visual obstruction in the first image frame and/orsecond image frame. Image processing may be applied to the first imageframe and/or second image frame based on a comparison between a firstarea of the first image frame corresponding to the region of interestand a second area of the second image frame corresponding to the regionof interest, and the first image frame and/or second image frame may beprovided for display to a user.

BRIEF DESCRIPTION OF THE FIGURES

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate various exemplary embodiments andtogether with the description, serve to explain the principles of thedisclosure.

FIG. 1 illustrates a medical system, according to aspects of the presentdisclosure.

FIG. 2 is a flow diagram of an exemplary method for processing medicalimages, according to aspects of the present disclosure.

FIG. 3 is a flow diagram of an exemplary method for determining a regionof interest in medical images, according to aspects of the presentdisclosure.

FIG. 4 is a flow diagram of an exemplary method for determining atemplate for object tracking in medical images, according to aspects ofthe present disclosure.

FIG. 5 is a flow diagram of an exemplary method for determining medicalimage enhancement, according to aspects of the present disclosure.

FIG. 6 illustrates an exemplary system that may be used in accordancewith techniques discussed in FIGS. 1-5, according to aspects of thepresent disclosure.

DETAILED DESCRIPTION

Examples of the present disclosure include systems and methods tofacilitate, and improve the efficiency and safety of minimally-invasivesurgeries. For example, aspects of the present disclosure may provide auser (e.g., a physician, medical technician, or other medical serviceprovider) with the ability to more easily identify and, thus, removekidney stones or other material from a patient's kidney or other organ.In some embodiments, for example, the present disclosure may be used inplanning and/or performing a flexible ureteroscope procedure, with orwithout laser lithotripsy. Techniques discussed herein may also beapplicable in other medical techniques, such as any medical techniqueutilizing an endoscope.

Reference will now be made in detail to examples of the presentdisclosure described above and illustrated in the accompanying drawings.Wherever possible, the same reference numbers will be used throughoutthe drawings to refer to the same or like parts.

The terms “proximal” and “distal” are used herein to refer to therelative positions of the components of an exemplary medical device orinsertion device. When used herein, “proximal” refers to a positionrelatively closer to the exterior of the body or closer to an operatorusing the medical device or insertion device. In contrast, “distal”refers to a position relatively further away from the operator using themedical device or insertion device, or closer to the interior of thebody.

Both the foregoing general description and the following detaileddescription are exemplary and explanatory only and are not restrictiveof the features, as claimed. As used herein, the terms “comprises,”“comprising,” or other variations thereof, are intended to cover anon-exclusive inclusion such that a process, method, article, orapparatus that comprises a list of elements does not include only thoseelements, but may include other elements not expressly listed orinherent to such a process, method, article, or apparatus. Additionally,the term “exemplary” is used herein in the sense of “example,” ratherthan “ideal.” As used herein, the terms “about,” “substantially,” and“approximately,” indicate a range of values within +/−5% of a statedvalue.

FIG. 1 illustrates a medical system 100 that includes a medical devicesuch as an endoscope or other medical imaging device/medical device 105,a network 110, user device(s) 115 that may include a display(s) 120 thatmay be viewed by a user/practitioner/physician/patient 125, andserver(s) 130 that may comprise a frame processor 135 and/or a templatematcher 140. The endoscope 105, user device(s) 115, and/or server 130may be wire connected (as shown), wirelessly connected, or otherwisecommunicatively coupled. Alternatively, functionality of the server 130may be performed on endoscope 105, user device 115, etc. The server 130,endoscope 105, and/or user device 115 may further comprise a singleelectronic device.

As shown in FIG. 1, endoscope 105 may be an insertion device such as,for example, a ureteroscope (e.g., LithoVue™ Digital FlexibleUreteroscope by Boston Scientific Corp.).

With endoscope 105 positioned within a patient, for example, through thepatient's urethra to a patient's kidney, a retrieval device (not shown)may be inserted to retrieve and remove material such as, for example, akidney stone, with or without using laser lithotripsy. The endoscope 105may record and/or transmit image and/or video data when inserted into apatient, and may have a light or other imaging source that may act todisplay images of the interior of a patient's vessels, organs, etc. Theendoscope 105 may further be equipped with a laser for performance oflaser lithotripsy, which may be used to remove, break up, or otherwisedestroy one or more organ obstructions, such as kidney stones.

Display 120 may be a single, or at least a dual display, with eithermultiple screens or multiple displays on one screen. In one example, oneof the displays may show an image or images currently or previouslyobtained by endoscope 105. The other display may show an image or videoobtained from one or more additional imaging devices 145, such as byX-ray, Magnetic Resonance Imaging, Computerized Tomography Scan,rotational angiography, ultrasound, or another appropriate internalimaging device. Alternatively, one of the displays 120 may show an imagemodified using one or more image enhancement techniques discussedherein, while another may display an unenhanced image. Alternatively,one of the displays 120 may show an image modified using one or moreenhancement techniques discussed herein, while another of the displays120 may show an image modified using one or more different enhancementtechniques discussed herein.

The software or applications, may manipulate, process, and interpretreceived images from imaging device 145 to identify the presence,location, and characteristics of a kidney stone or other material. Aswill be discussed further herein, the frame processor 135 and/ortemplate matching applications 140 may process and enhance receivedimages from endoscope 105.

The physician may insert endoscope 105 into a patient when performing amedical procedure such as a lithotripsy to remove a kidney stone. Thedisplay 120 may become partially or completely obscured by pieces ofkidney stone or other floating particulate matter, for example, whenilluminated by a light on the endoscope 105. Additionally, a flashcreated by a laser or other light source emitted from the endoscope 105may cause surgeons or technicians to lose track of the kidney stone orother object of the medical procedure. The difficulty in tracking thekidney stone or object of the procedure may increase the time ofperforming the medical procedure, may increase the rate of errors of themedical procedure, and may increase the cognitive load in maintainingvisual track of the object.

FIG. 2 is a flow diagram of an exemplary method for processing medicalimages, according to aspects of the present disclosure. A source ofvideo or image frames 205, which may be any medical device, such as anendoscope 105 or imaging device 145, may provide frames to signal in210. The frames may be provided to a frame handler 215, which may storea plurality of frames. One or more frames 220 may be provided to a frameprocessor 135, which may produce one or more processed frames 230. Theprocessed frames 230 may be provided to the signal out 235, which may beshown on display 120.

The signal in 210 may be a software handler that may transmit that a newframe has been received. The frame handler 215 may either directly senda frame via the signal out 235 to a display 120, or it may send one ormore frames to the frame processor 135. As will be discussed elsewhereherein, the frame processor 135 may perform distraction reduction and/ortemplate matching techniques. The frame handler 215 may also send theoriginal frame to the display 120, and also send a copy of the frame tothe frame processor 135. The processed frame 230 may be received andalso forwarded to the display 120. This may allow for the original frameto be displayed alongside the processed frame 230 at the display 120.Alternatively, the frame handler 215 may send the source frame 220 tothe frame processor 135, and the frame processor may return a processedframe 230 that comprises a dual display of the original and enhancedframe. Accordingly, the processed frame 230 may be larger than thesource frame. The frame processor 135 may further add buttons or otheruser interface elements to the processed frame 230.

Although techniques discussed herein are discussed as happening on theframe processor 135, which may be depicted as being located on a singledevice, any of the functions of the frame processor may be spread acrossany number of devices, for example, any of the devices depicted insystem 100. Further, one or more of the signal in 210, frame handler215, and/or signal out 235 may be housed on one or more servers 130, orany of the other devices pictured on system 100.

FIG. 3 is a flow diagram of an exemplary method for distractiondeduction, according to aspects of the present disclosure. A pluralityof frames may be received from a frame source 305. The frame source maycomprise an endoscope 105 or other medical imaging device 145. One ormore frames may be accumulated at a color frame buffer 310 and/or agrayscale frame buffer 315. A plurality of frames may be accumulated forcomparison. By comparing multiple frames with each other, a backgroundmay be discerned and distinguished from a visual obstruction. The visualobstruction may be a reflection, glare, light source, piece of dust,debris, particle, piece of kidney or gall stone or other calculus, etc.The visual obstruction may also have an associated brightness orintensity that is beyond a threshold. Using techniques discussed herein,the visual obstruction may be identified as a region of interest, andmay receive processing to remove or mitigate the extent or severity ofthe obstruction.

When a new frame is received from the frame source 305, a copy may bestored in the color frame buffer 310 and/or the grayscale frame buffer315. Frames in the color frame buffer 310 may have a plurality ofchannels for a plurality of colors, for example, three channels for red,green and blue. A copy of the frame may be stored in grayscale framebuffer 315. The grayscale frame buffer 315 and/or the color frame buffer310 may be used to determine one or more regions of interest in theframe, which may comprise one or more visual obstructions.

A received color frame may be converted to grayscale for storage in thegrayscale frame buffer 315. Conversion may comprise combining two ormore of the color channels to form a grayscale frame. This may be done,at least in part, because different color channels in color frames maydisagree about whether there is a visual obstruction (e.g., lightintensity beyond a threshold, piece of debris beyond a size threshold,etc.). A combined-channel frame might not have such disagreements, sincethere is only one channel, yet the information from the multiplechannels may still be present in the combined-channel frame.

Alternatively, a region of interest may be identified withoutdetermining grayscale frames. Any color channel which reports a visualobstruction according to techniques discussed herein may be used todetermine a region of interest, even if there is disagreement from othercolor channels about whether there is any region of interest.

The region of interest mask generator 320 may receive frames from thegrayscale frame buffer 315 and/or the color frame buffer 310. The regionof interest mask generator 320 may determine areas (regions of interest)with intensity changes that may be removed from the presented frame. Aplurality of received frames, which may be consecutive frames, may becompared, and the common features may be subtracted. For example, if acurrent frame 322 is being processed to determine a region of interest,it may be compared with preceding frame 321 and the subsequent/laterframe 323. Common features, or features that are determined to besimilar within a predetermined threshold, of the frames may besubtracted from each other. Two processed frames may be generated, thefirst a subtraction of the prior frame 321 and the current frame 322,and the second a subtraction of the subsequent frame 323 and the currentframe 322. The two processed frames may then be added to each other. Anyobjects remaining may be designated as region(s) of interest 324.

The common features may be the background, and thus, after thesubtraction, only objects moving more quickly than the background, suchas pieces of debris and other visual obstructions, may remain. These oneor more visual obstructions may be designated as a region of interestand a region of interest mask may be applied.

Visual obstructions may also be objects with a light intensity that isbeyond a threshold. For example, a reflection of a light or laser beyonda brightness/intensity threshold may not come from a particle or otherobject moving near the endoscope, but rather may come from lightreflecting off the kidney stone itself, vessel/tissue/organ wall, orsome other object that may not subtract out from nearby frames. Thus,regions of interest may also or alternatively be designated for anyregion with a light intensity/brightness exceeding a predeterminedthreshold. By comparing nearby frames, before and/or after the framereceiving processing, this type of visual obstruction may be identified.For example, a current frame 322 may be the frame receiving processing.The current frame 322 may be compared to a frame prior in time 321 thatdid not have the intense light visual obstruction. The two frames may besubtracted to determine a first subtracted frame. The current frame 323may then be compared to a frame afterwards in time 323 that did not haveintense light visual obstruction. The two frames may be subtracted todetermine a second subtracted frame. The two subtracted frames may thenbe added together to determine the region of interest mask. This processmay be repeated with more frames from which subtractions are performed.Alternatively, the determination of the region of interest may beperformed by only comparing the frame to be processed to one otherframe.

The one or more frames may be provided with the identified one or moreregions or interest 324 to the region of interest comparator 325. Nowthat the region(s) of interest is determined, it may be analyzedrelative to one or more color channels of the associated color versionof the frame. At a first color channel, for example red, two or moreframes may be analyzed. For example, the frame being processed 322 maybe compared with prior frame 321 and subsequent frame 323. Imagecharacteristics may be compared of the determined regions of interest324 across a plurality of respective frames. For example, imagecharacteristics the region of interest 324 of the current frame 322 maybe compared to the corresponding region of interest 332 of prior frame321. The region of interest 332 may cover the same area of the frame asthe region of interest 324. Image characteristics of the region ofinterest 324 of the current frame 322 may further be compared to theregion of interest 342 of subsequent frame 323. For example, the imagecharacteristics compared may be brightness, intensity, amount ofintensity change relative to other frames, deviation from averagebrightness across a predetermined number of frames, motion pattern,texture, intensity histogram, entropy, etc.

In one embodiment, the intensity of a color channel across multipleframes may be compared, and the lowest, median, or average intensity maybe determined. For example, in the red channel, pixels, on average, inregion of interest 332 may have an intensity of 5, while region ofinterest 324 may have an intensity of 95, and region of interest 342 mayhave an intensity of 25. The plurality of frames may have a visualobstruction that is very dark or very bright. Accordingly, the medianvalue of the intensity across multiple frames may be selected. Thepixels of the region of interest with the median value may be made toreplace the pixels of the region of interest of the current frame 322.This determination may be made for the other color channels, for examplegreen and blue. It is possible that the regions of interest on somecolor channels will be replaced with that of another frame, while theregions of interest on other color channels will remain uncorrected. Thecolor channels may be processed in this manner until all channels have aprocessed region of interest, as necessary. In the example of FIG. 3,region of interest 342 of subsequent frame 323 may replace the region ofinterest 324 of the current frame 322, as shown in FIG. 3 as region ofinterest 345. In this manner, a bright flash or dark obstruction in thecurrent frame may be replaced to mitigate or eliminate the visualobstruction.

A possible side effect of replacing regions of interest, as describedabove, is that hard or artificial edges (halos) may appear around thereplaced regions. This may distort the viewer's perception of the trueshape of the object receiving image correction, and may give the viewerthe impression of edges that are not actually present in the body of thepatient.

To mitigate or eliminate this problem, after the region of interest isdetermined, at 350 an edge 352 of the region of interest may bedetermined. This edge 352 may be of a predetermined thickness, or may bebased on the dimensions of the region of interest. For example, as theregion of interest gets larger, the edge 352 may automatically bedetermined to be thicker. The edges may be determined usingmorphological operations (for example, dilation and erosion operations).The region of interest edge may be placed over the current frame 355with the replaced region of interest 357. The edge of the replacedregion of interest 357 may be removed. The region of interest edge maybe in-painted, or may have a color gradient from the inside edge to theoutside edge applied such that the “halo” of the processed current frameis removed/smoothed out, and any harsh edges that may cause visualdistraction are removed. The color gradient might not only be afirst-degree gradient, but also a second derivative gradient to helpsmooth the color transition from the inside to the outside of the edge352. After these techniques are applied, a processed frame 360, withcorrected edge 362, may be provided for display to a user.

FIG. 4 is a flow diagram of an exemplary method for determining atemplate for object tracking in medical images, according to aspects ofthe present disclosure. As discussed above, it may be difficult for anendoscope operator to track a target object or tissue, such as a kidneystone. In addition to visual obstructions, there is movement of theendoscope and other effects that may increase the tracking difficultyand thereby the cognitive load of the endoscope operator. Whileprocessing frames to reduce or remove visual obstructions may make theprocess easier, it may help to highlight or otherwise indicate thetarget tissue or object on the display automatically. For example, a boxor outline may be placed around the target object, such as a kidneystone. FIG. 4 discloses techniques of template matching 142, which maybe performed separately from, or in addition to, distraction deductiontechniques discussed elsewhere herein.

At frame 0 (405), the frame may be provided to a trained template system410. The trained template system 410 may have been trained with imagesof the target object, such as images of kidney stones. The trainedtemplate system may return a portion of frame 0 corresponding to thetarget object, for example, the portion of frame 0 containing an imageof the kidney stone, indicated as template 415. Template 415 may be usedto quickly and automatically identify the same target object insubsequent frame 1 (420). For the given template and target frame,various image features may be determined (intensity, gradient, etc.) forboth, which may be used to determine if a match exists. The targetobject in frame 1 may be somewhat different, as it may have rotated,changed shape (been fragmented), move closer or further from the camera,etc. That said, if template 415 matches any region of frame 1 within apredetermined tolerance/confidence threshold, the matching region may beassumed to be the target object in the subsequent frame. In this manner,using templates taken from prior frames, an object may be tracked acrossa plurality of frames. As discussed above, a bounding box, a circle,pointer, or any other indicator may be placed around the target objectto allow for easier user tracking of the object. In addition, anindicator of the confidence of the match may also be determined and/ordisplayed.

A portion of frame 1 may be used to generate template 425. Template 425may be used to locate the target object in subsequent frame 2 (430). Theportion of frame 2 containing the target object may be used to generatetemplate 435. Using templates may be faster and computationally lessintensive than providing each frame to the trained template system 410for tracking the target object. Accordingly, templates might be usedpreferentially, unless the target object cannot be tracked within apredetermined confidence. Template 435 may be used to recognize thetarget object in frame 3 (440).

The templates may be compared rapidly against each portion of the frameto determine if there is a match within a predetermined threshold orconfidence. However, there might not be a match to within apredetermined threshold or confidence. For example, a kidney stone maybe fragmented and be shaped substantially differently from one frame tothe next. If, for example, the target object is not recognizable withina tolerance using a template from the prior frame, the frame, such as aframe 3, may be provided again to the trained template system 410. Thetrained template system 410 may return template 445, which may be usedto recognize the target object in frame 4 (450), and so on.

In addition, a buffer of templates may be stored from prior frames. Ifan object occludes the endoscope 105 or other medical imaging device, ifonly templates of the immediately prior frame were used to track thetarget object, tracking of the target object might quickly fail. In theevent that the target object is not recognized within a predeterminedconfidence, additional prior templates may be analyzed to search for amatch.

FIG. 5 is a flow diagram of an exemplary method for determining medicalimage enhancement, according to aspects of the present disclosure. Atstep 505, a first image frame and a second image frame may be receivedfrom a medical imaging device. At step 510, a region of interest may bedetermined by subtracting the first image frame from the second imageframe, the region of interest corresponding to a visual obstruction inthe first image frame and/or second image frame. At step 515, imageprocessing may be applied to the first image frame and/or second imageframe based on a comparison between a first area of the first imageframe corresponding to the region of interest and a second area of thesecond image frame corresponding to the region of interest. At step 520,the first image frame and/or second image frame may be provided fordisplay to a user.

FIG. 6 illustrates an exemplary system that may be used in accordancewith techniques discussed in FIGS. 1-5, according to aspects of thepresent disclosure. FIG. 6 is a simplified functional block diagram of acomputer that may be configured as server 130, endoscope 105, imagingdevice 145, and/or user device 115, according to exemplary embodimentsof the present disclosure. Specifically, in one embodiment, any of theuser devices, servers, etc., discussed herein may be an assembly ofhardware 600 including, for example, a data communication interface 620for packet data communication. The platform also may include a centralprocessing unit (“CPU”) 602, in the form of one or more processors, forexecuting program instructions. The platform may include an internalcommunication bus 608, and a storage unit 606 (such as ROM, HDD, SDD,etc.) that may store data on a computer readable medium 622, althoughthe system 600 may receive programming and data via networkcommunications. The system 600 may also have a memory 604 (such as RAM)storing instructions 624 for executing techniques presented herein,although the instructions 624 may be stored temporarily or permanentlywithin other modules of system 600 (e.g., processor 602 and/or computerreadable medium 622). The system 600 also may include input and outputports 612 and/or a display 610 to connect with input and output devicessuch as keyboards, mice, touchscreens, monitors, displays, etc. Thevarious system functions may be implemented in a distributed fashion ona number of similar platforms, to distribute the processing load.Alternatively, the systems may be implemented by appropriate programmingof one computer hardware platform.

The disclosed techniques may help enable efficient and effectiveprocedures to breakup and/or remove material from a patient's organ. Inparticular, the user may easily view the processed frames to assistwith, for example, removing kidney stones within the patient's kidney.The image may be clearer, with less visual obstructions, and the targetkidney stone may be easier to track due to an indicator following itslocation. Therefore, in the kidney stone example, the user may moreefficiently remove the kidney stones from specific locations within thepatient's kidney.

Moreover, while examples discussed in this disclosure are commonlydirected to ureteroscopic kidney stone removal, with or withoutlithotripsy, it is further contemplated that the systems and proceduresdiscussed herein may be equally applicable to other material removalprocedures. For example, the systems and methods discussed above may beused during a percutaneous nephrolithotomy/nephrolithotripsy (PCNL) toplan for a procedure and mid-procedure to locate any missed kidneystones. The systems and methods discussed above may also be used to planfor or conduct procedures to remove ureteral stones, gallstones, bileduct stones, etc.

While principles of the present disclosure are described herein withreference to illustrative examples for particular applications, itshould be understood that the disclosure is not limited thereto. Thosehaving ordinary skill in the art and access to the teachings providedherein will recognize additional modifications, applications,embodiments, and substitution of equivalents all fall within the scopeof the features described herein. Accordingly, the claimed features arenot to be considered as limited by the foregoing description.

We claim:
 1. A method for processing electronic images from a medicaldevice, comprising: receiving a first image frame and a second imageframe from a medical device; determining a region of interest bysubtracting the first image frame from the second image frame, theregion of interest corresponding to a visual obstruction in the firstimage frame and/or second image frame, the visual obstruction comprisinga reflection, glare, piece of debris, and/or calculus; applying imageprocessing to the first image frame and/or second image frame based on acomparison between a first area of the first image frame correspondingto the region of interest and a second area of the second image framecorresponding to the region of interest; providing the first image frameand/or second image frame for display to a user; receiving a third imageframe from the medical device; determining a first pixel valueassociated with the first area of the first image frame corresponding tothe region of interest; determining a second pixel value associated withthe second area of the second image frame corresponding to the region ofinterest; determining a third pixel value associated with a third areaof the third image frame; applying image processing to the second areaof the second image frame corresponding to the region of interest, basedon a comparison of the first pixel value, the second pixel value, andthe third pixel value, to mitigate or eliminate the visual obstruction;determining a border of a predetermined thickness around the region ofinterest; and applying a color gradient across the border of thepredetermined thickness around the region of interest.
 2. The method ofclaim 1, wherein subtracting the first image frame from the second imageframe comprises removing regions from consideration for the region ofinterest if the regions are similar beyond a predetermined threshold inboth the first image frame and the second image frame.
 3. The method ofclaim 1, further comprising: generating a grayscale first image framebased on the first image frame; generating a grayscale second imageframe based on the second image frame; and determining the region ofinterest based on the grayscale first image frame and the grayscalesecond image frame.
 4. The method of claim 1, wherein determining theregion of interest further comprises: receiving a third image frame fromthe medical device; and determining the region of interest by:subtracting the first image frame from the second image frame to form afirst subtracted image frame; subtracting the second image frame fromthe third image frame to form a second subtracted image frame; andadding the first subtracted image frame and the second subtracted imageframe.
 5. The method of claim 1, wherein applying image processing tothe second area of the second image frame further comprises determininga median pixel by comparing the first pixel value, the second pixelvalue, and the third pixel value; upon determining that the first pixelvalue is the median pixel, replacing the second area of the second imageframe corresponding to the region of interest with the first area of thefirst image frame corresponding to the region of interest; and upondetermining that the third pixel value is the median pixel, replacingthe second area of the second image frame corresponding to the region ofinterest with the third area of the third image frame corresponding tothe region of interest.
 6. The method of claim 5, wherein the steps ofdetermining the median pixel and replacing the second area of the secondimage frame are performed one color channel at a time.
 7. The method ofclaim 1, further comprising: determining a first template associatedwith an object of interest in the first image frame, the first templatecomprising a portion of the first image frame depicting the object ofinterest; and determining a location of the object of interest in thesecond image frame based on the first template.
 8. The method of claim7, wherein determining the location of the object of interest in thesecond image frame further comprises: comparing the first template witha plurality of regions of the second image frame; and upon locating aregion of the second image frame that matches the first template withina predetermined tolerance, associating the region of the second imageframe with the object of interest.
 9. The method of claim 7, furthercomprising: providing an indication of the region of the second imageframe with the object of interest for display to the user.
 10. A systemfor processing electronic images from a medical device, comprising: adata storage device storing instructions for processing electronicimages; and a processor configured to execute the instructions toperform a method for processing electronic images, the method including:receiving a first image frame and a second image frame from a medicaldevice; determining a region of interest by subtracting the first imageframe from the second image frame, the region of interest correspondingto a visual obstruction in the first image frame and/or second imageframe, the visual obstruction comprising a reflection, glare, piece ofdebris, and/or calculus; applying image processing to the first imageframe and/or second image frame based on a comparison between a firstarea of the first image frame corresponding to the region of interestand a second area of the second image frame corresponding to the regionof interest; providing the first image frame and/or second image framefor display to a user; receiving a third image frame from the medicaldevice; determining a first pixel value associated with the first areaof the first image frame corresponding to the region of interest;determining a second pixel value associated with the second area of thesecond image frame corresponding to the region of interest; determininga third pixel value associated with a third area of the third imageframe; applying image processing to the second area of the second imageframe corresponding to the region of interest, based on a comparison ofthe first pixel value, the second pixel value, and the third pixelvalue, to mitigate or eliminate the visual obstruction; determining aborder of a predetermined thickness around the region of interest; andapplying a color gradient across the border of the predeterminedthickness around the region of interest.
 11. The system of claim 10,wherein subtracting the first image frame from the second image framecomprises removing regions from consideration for the region of interestif the regions are similar beyond a predetermined threshold in both thefirst image frame and the second image frame.
 12. The system of claim10, the method executed by the system further comprising: generating agrayscale first image frame based on the first image frame; generating agrayscale second image frame based on the second image frame; anddetermining the region of interest based on the grayscale first imageframe and the grayscale second image frame.
 13. The system of claim 10,wherein determining the region of interest further comprises:determining the region of interest by: subtracting the first image framefrom the second image frame to form a first subtracted image frame;subtracting the second image frame from the third image frame to form asecond subtracted image frame; and adding the first subtracted imageframe and the second subtracted image frame.
 14. The system of claim 10,the method executed by the system further comprising: determining afirst template associated with an object of interest in the first imageframe, the first template comprising a portion of the first image framedepicting the object of interest; and determining a location of theobject of interest in the second image frame based on the firsttemplate.
 15. A non-transitory computer-readable medium storinginstructions that, when executed by a computer, cause the computer toperform a method for processing electronic images from a medical device,the method including: receiving a first image frame and a second imageframe from a medical device; determining a region of interest bysubtracting the first image frame from the second image frame, theregion of interest corresponding to a visual obstruction in the firstimage frame and/or second image frame, the visual obstruction comprisinga reflection, glare, piece of debris, and/or calculus; applying imageprocessing to the first image frame and/or second image frame based on acomparison between a first area of the first image frame correspondingto the region of interest and a second area of the second image framecorresponding to the region of interest; providing the first image frameand/or second image frame for display to a user; receiving a third imageframe from the medical device; determining a first pixel valueassociated with the first area of the first image frame corresponding tothe region of interest; determining a second pixel value associated withthe second area of the second image frame corresponding to the region ofinterest; determining a third pixel value associated with a third areaof the third image frame; and applying image processing to the secondarea of the second image frame corresponding to the region of interestby: comparing the first pixel value, the second pixel value, and thethird pixel value, determining a median pixel based on the comparison ofthe first pixel value, the second pixel value, and the third pixelvalue; upon determining that the first pixel value is the median pixel,replacing the second area of the second image frame corresponding to theregion of interest with the first area of the first image framecorresponding to the region of interest; and upon determining that thethird pixel value is the median pixel, replacing the second area of thesecond image frame corresponding to the region of interest with thethird area of the third image frame corresponding to the region ofinterest, wherein the steps of determining the median pixel andreplacing the second area of the second image frame are performed onecolor channel at a time.